Feature extractor:  \(f_\text{enc}\)  is implemented as a 2-stack hourglass network [1]} following PIFu [2]}. Given the instance mask, we take out the object of interest in the picture and resize it to \(256\times 256\)  before providing it as input to \(f_\text{enc}\) . The output feature map has dimensions of \(128\times 128\times 256\)  of spatial resolution \(128\times 128\)  and feature dimension \(K=256\) .
